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  • 1
    Monograph available for loan
    Monograph available for loan
    New York : SIAM
    Call number: M 12.0258
    Description / Table of Contents: Contents: 1. Introduction and motivation; 2. Meet the Fredholm integral equation of the first kind; 3. Getting to business: discretizations of linear inverse problems; 4. Computational aspects: regularization methods; 5. Getting serious: choosing the regularization parameter; 6. Toward real-world problems: iterative regularization; 7. Regularization methods at work: solving real problems; 8. Beyond the 2-norm: the use of discrete smoothing norms; Appendix A. Linear algebra stuff; Appendix B. Symmetric Toeplitz-plus-Hankel matrices and the DCT; Appendix C. Early work on 'Tikhonov regularization';
    Description / Table of Contents: This book gives an introduction to the practical treatment of inverse problems by means of numerical methods, with a focus on basic mathematical and computational aspects. To solve inverse problems, we demonstrate that insight about them goes hand in hand with algorithms
    Type of Medium: Monograph available for loan
    Pages: xii, 213 S.
    ISBN: 9780898716962
    Series Statement: Fundamentals of algorithms
    Classification:
    Mathematics
    Location: Upper compact magazine
    Branch Library: GFZ Library
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  • 2
    Monograph available for loan
    Monograph available for loan
    Philadelphia, Pa. : Soc. for Industrial and Applied Mathematics
    Call number: M 03.0397
    Type of Medium: Monograph available for loan
    Pages: xvi, 247 S.
    ISBN: 0898714036
    Series Statement: SIAM monographs on mathematical modeling and computation
    Classification:
    Mathematics
    Location: Upper compact magazine
    Branch Library: GFZ Library
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  • 3
    Monograph available for loan
    Monograph available for loan
    Berlin [u.a.] : Springer
    Associated volumes
    Call number: 4/M 00.0369
    In: Lecture notes in earth sciences
    Type of Medium: Monograph available for loan
    Pages: X, 304 S.
    ISBN: 3540659161
    Series Statement: Lecture notes in earth sciences 92
    Classification:
    C.1.6.
    Location: Reading room
    Branch Library: GFZ Library
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    BIT 27 (1987), S. 534-553 
    ISSN: 1572-9125
    Keywords: 65F20 ; 65F30 ; truncated SVD ; regularization in standard form ; perturbation theory for truncated SVD ; numerical rank
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The truncated singular value decomposition (SVD) is considered as a method for regularization of ill-posed linear least squares problems. In particular, the truncated SVD solution is compared with the usual regularized solution. Necessary conditions are defined in which the two methods will yield similar results. This investigation suggests the truncated SVD as a favorable alternative to standard-form regularization in cases of ill-conditioned matrices with well-determined numerical rank.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    BIT 29 (1989), S. 491-504 
    ISSN: 1572-9125
    Keywords: 65F20 ; 65F30 ; Ill-posed problems ; regularization ; generalized SVD ; perturbation theory ; generalized cross-validation ; transformation to standard form
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The purpose of this paper is to analyze Tikhonov regularization in general form by means of generalized SVD (GSVD) in the same spirit as SVD is used to analyze standard-form regularization. We also define a truncated GSVD solution which is of interest in its own right and which sheds light on regularization as well. In addition, our analysis gives insight into a particular numerical method for solving the general-form problem via a transformation to standard form.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    BIT 30 (1990), S. 658-672 
    ISSN: 1572-9125
    Keywords: 65F30 ; 65F20 ; Ill-posed problems ; Tikhonov regularization ; discrete Picard condition ; generalized SVD
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We investigate the approximation properties of regularized solutions to discrete ill-posed least squares problems. A necessary condition for obtaining good regularized solutions is that the Fourier coefficients of the right-hand side, when expressed in terms of the generalized SVD associated with the regularization problem, on the average decay to zero faster than the generalized singular values. This is the discrete Picard condition. We illustrate the importance of this condition theoretically as well as experimentally.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Numerische Mathematik 70 (1995), S. 453-471 
    ISSN: 0945-3245
    Keywords: Mathematics Subject Classification (1991):65F25, 65F30
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Summary. Rank-revealing decompositions are favorable alternatives to the singular value decomposition (SVD) because they are faster to compute and easier to update. Although they do not yield all the information that the SVD does, they yield enough information to solve various problems because they provide accurate bases for the relevant subspaces. In this paper we consider rank-revealing decompositions in computing estimates of the truncated SVD (TSVD) solution to an overdetermined system of linear equations $A x \approx b$ , where $A$ is numerically rank deficient. We derive analytical bounds which show how the accuracy of the solution is intimately connected to the quality of the subspaces.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Numerical algorithms 6 (1994), S. 1-35 
    ISSN: 1572-9265
    Keywords: Regularization ; ill-posed problems ; ill-conditioning, Matlab ; Subject classification ; AMS(MOS) 65F30 ; 65F20
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract The package REGULARIZATION TOOLS consists of 54 Matlab routines for analysis and solution of discrete ill-posed problems, i.e., systems of linear equations whose coefficient matrix has the properties that its condition number is very large, and its singular values decay gradually to zero. Such problems typically arise in connection with discretization of Fredholm integral equations of the first kind, and similar ill-posed problems. Some form of regularization is always required in order to compute a stabilized solution to discrete ill-posed problems. The purpose of REGULARIZATION TOOLS is to provide the user with easy-to-use routines, based on numerical robust and efficient algorithms, for doing experiments with regularization of discrete ill-posed problems. By means of this package, the user can experiment with different regularization strategies, compare them, and draw conclusions from these experiments that would otherwise require a major programming effert. For discrete ill-posed problems, which are indeed difficult to treat numerically, such an approach is certainly superior to a single black-box routine. This paper describes the underlying theory gives an overview of the package; a complete manual is also available.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    Springer
    Numerical algorithms 2 (1992), S. 371-391 
    ISSN: 1572-9265
    Keywords: AMS(MOS) 65F25 ; 65F20 ; Rank-revealing QR factorization ; numerical rank ; block algorithm
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We present a block algorithm for computing rank-revealing QR factorizations (RRQR factorizations) of rank-deficient matrices. The algorithm is a block generalization of the RRQR-algorithm of Foster and Chan. While the unblocked algorithm reveals the rank by peeling off small singular values one by one, our algorithm identifies groups of small singular values. In our block algorithm, we use incremental condition estimation to compute approximations to the nullvectors of the matrix. By applying another (in essence also rank-revealing) orthogonal factorization to the nullspace matrix thus created, we can then generate triangular blocks with small norm in the lower right part ofR. This scheme is applied in an iterative fashion until the rank has been revealed in the (updated) QR factorization. We show that the algorithm produces the correct solution, under very weak assumptions for the orthogonal factorization used for the nullspace matrix. We then discuss issues concerning an efficient implementation of the algorithm and present some numerical experiments. Our experiments show that the block algorithm is reliable and successfully captures several small singular values, in particular in the initial block steps. Our experiments confirm the reliability of our algorithm and show that the block algorithm greatly reduces the number of triangular solves and increases the computational granularity of the RRQR computation.
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    Springer
    Numerical algorithms 20 (1999), S. 165-194 
    ISSN: 1572-9265
    Keywords: rank-revealing decompositions ; rank deficiency ; numerical rank ; up- and downdating ; Matlab ; 65F25 ; 65F20
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We describe a Matlab 5.2 package for computing and modifying certain rank-revealing decompositions that have found widespread use in signal processing and other applications. The package focuses on algorithms for URV and ULV decompositions, collectively known as UTV decompositions. We include algorithms for the ULLV decomposition, which generalizes the ULV decomposition to a pair of matrices. For completeness a few algorithms for computation of the RRQR decomposition are also included. The software in this package can be used as is, or can be considered as templates for specialized implementations on signal processors and similar dedicated hardware platforms.
    Type of Medium: Electronic Resource
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